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The Oakland Athletics completed their second-half collapse in true Oakland fashion by failing somehow to advance in the postseason against the Royals. For a season in which Beane went all-in by trading future potential for current performance, in which the A’s began the year an unstoppable, historic juggernaut, the inglorious ending has to smart.

The A’s of this year embodied one of the most beloved playoff myths, that the second half of a team’s performance predicts how that team will do in the playoffs. I say “myth” because, at least in the aggregate, there is little or no evidence in support of this idea, and so it has been debunked on numerous occasions. And yet, there may not be a better example of that phenomenon in action than this team, which roared out to an incredible start to the season, on pace to challenge run-differential records, only to buckle in the second half, barely making the playoffs.

My intuition wants me to believe that the A’s collapse was inevitable somehow. It’s frustrating to look at a team like the A’s, made cleverly and on a shoe-string budget by a sabermetric hero, failing for no other reason than six inches of Josh Donaldson's positioning and tremendously poor injury luck. Naturally, I want a reason, some scapegoat, or at least a clue, as to why these promising A’s folded so readily.

Whatever the ultimate cause, Oakland’s collapse is primarily on the offense, whose production fell by something like a run and a half in the second half of the season. The Oakland lineup is loaded with potent hitters, and it made no sense for them to fizzle. One can’t predict ball.

I should note here that the offense performed perfectly capably in the wild-card game, putting up eight runs against the excellent combination of James Shields and the KC bullpen (with a special guest appearance by Yordano Ventura). For a night, whatever offensive struggles ailed them were less of a concern than Jon Lester’s inability to throw over to first and Ned Yost’s Retro Small-Ball Attack. Even so, Oakland never would have had to be in the wildcard play-in if their hitters had kept up their performance in the first half, so I’ll focus here on that offense.

There might be a clue to the Oakland breakdown in the approach pitchers used against them as the year went on. Pitch selection is one element of the overall approach, and while different pitchers may possess different repertoires, we can roughly divide all pitches into fastballs and not-fastballs. Generally, players who see fewer fastballs are younger and drive pitches with more authority. Conversely, players who see more fastballs are older and less powerful.

The league average fastball percentage is about 55 percent. For the first three months of the 2014 season, Oakland’s core group of regulars maintained a fastball percentage of 54.1 percent, just a smidge under the average. The group had good power (SLG’s of .412, .421, .383 by month) and plate discipline, and it wasn’t on some fluky BABIP (.298, .265, .301). Everything was going well and in the proper order.

Then, something weird happened. Pitchers started throwing the Oakland A’s many fewer fastballs.

Description: C:UsersRKGoogle DriveBaseball Prospectusarticlesthe Collapse of the AthleticsTeam_Fastball_Frequency.png

Charting the frequency of fastballs by month, you can see Oakland bouncing around in the normal zone of ~.55 in the first three months of the season. July rolls around, and abruptly, fastball frequency falls 8 points. It recovered to a reasonable level in August, but went back to the bottom in September.

Overall, the fastball frequency of the A’s hitters in the first three months of the season was 54.1 percent, and in the last three months, 52.2 percent. It’s not a tremendous decrease, but keep in mind that we’re looking at thousands of pooled pitches, and that the numbers are aggregated across hitters. If you look at individual A’s hitters, the differences get even more pronounced.

Description: C:UsersRKGoogle DriveBaseballIndividual_Fastball_Differences.png

From June on, all but Alberto Callaspo (black line with blue points) saw their frequencies drop radically, some by more than 10 percentage points. Josh Donaldson, for example (LOESS smoothed trend):

Description: C:UsersRKGoogle DriveBaseballDonaldson_FFreq.png

Or Brandon Moss:

Description: C:UsersRKGoogle DriveBaseballBMoss_FFreq.png

Even a player who left the team midseason, Yoenis Cespedes, sees his fastball frequency drop like a stone:

Description: C:UsersRKGoogle DriveBaseballCespedes_FFreq.png

The difference is sufficiently dramatic on the team level that it’s unlikely to have occurred by pure chance alone. If you draw a set of simulated lineups at random from players across the league, and ask how often these simulated lineups dropped as much fastball frequency as the A’s did, you find that it never happens. In other words, the drop in fastball propensity is to a statistically significant degree.

It’s not as though they faced fastball-happy hurlers in the first half and fastball-phobic throwers in the second. If you look at the pitchers the A’s faced in the first and second halves and ask how many fastballs they threw, there’s no difference. So as far as the pitchers who went up against the A’s, there was no predilection for the second-half hurlers to avoid the fastball against non-Oakland teams.

You may be wondering whether the drop off in fastball frequency might be related to the loss of one Yoenis Cespedes, slugger of some repute. Others have advanced the argument that Cespedes was somehow the linchpin of the Oakland offense, the crucial hitter whose presence enabled the rest of the batting order to perform optimally.

Perhaps I’ve simply re-discovered lineup protection, and really the whole time Cespedes was setting up his teammates with fastballs. That doesn’t appear to be the case, however; the timing doesn’t fit. The A’s fastball frequencies started their descent in July, when Cespedes was still on the team (he was traded on July 31st). It did continue in Cespedes’ absence, but it started before he left.

In addition, I usually think of lineup protection as altering the location of pitches more than their pitch types. I looked at the zone distance of all the pitches the A’s saw in the first and second halves, which is a proxy for how feared the A’s hitters were by opposing pitchers. There was no meaningful difference between halves. Zone distance did fall, but by only a tenth of an inch, which hardly seems enough to explain the A’s offensive blues.

Here’s the part where, ideally, we’d like to interpret what the decrease in fastball frequency means. The trouble is I’m not really sure how to do that. One might presume that the opposing teams chose rationally to decrease their fastball frequency because they thought that either 1) Oakland was doing especially well against fastballs or 2) Oakland was doing especially poorly against non-fastballs. However, perusing stats by pitch type doesn’t portray the Oakland hitters as feasting on the fastball or, conversely, being lost against breakers. Oakland did do well against all types of fastballs, but good-hitting teams generally do well against fastballs, or else they wouldn’t be so good.

A major caveat, however, is that breaking up outcomes by pitch type is unreliable and difficult. Since pitches play off each other in complex ways, a pitch which on the surface looks like a negative outcome may set up a weak groundout in the next throw. More broadly, it may be that the A’s truly struggle against curveballs and sliders, but in a way which doesn’t manifest obviously in the statistics. That’s an area crying out for further research and follow-up.

I can say confidently that the A’s saw a vastly decreased fastball frequency, and that it seems concerted and consistent enough to be a non-random difference. In other words, this change in approach looks like a calculated maneuver on the part of the opposing teams. But why they employed this shift is anybody’s guess.

In a way, analysts of baseball are often stuck picking up the breadcrumbs that the teams leave behind in PITCHf/x or other datasets. It looks like there’s a trail here somehow. That drop in fastball frequency looks deliberate enough to be a plan of attack, one which teams adopted against the A’s, and maybe that says something about the frailty of their first half success. On the other hand, maybe I just spent enough time and energy looking for an explanation where there isn’t one that I succeeded in finding a statistically improbable oddity. The trouble with intuition is that sometimes things really do happen just by chance.

Thank you for reading

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JoshC77
10/02
Interesting observations made here. I'm wondering if this is some kind of reaction to improving pitch counts against Oakland. I would expect that the raw pitch counts per PA would drop as FB frequency increases, so that may not be particularly useful in finding an explanation.

However, were the A's particularly good at working pitchers into deep counts (relative to league average) in the first half of the season? If so, perhaps they were good at exploiting those 3-0 or 3-1 offerings (thus having an above average BA against deep count offerings). To mitigate that, perhaps teams realized getting ahead of them earlier in the AB would be of greater benefit (thus an increase in FB usage). Looking at data for pitches/PA and team performance in deep counts might shed some additional light on this.
markpadden
10/02
Good point. One possible causal chain: A's hitters perform worse --> Underperforming hitters get into worse batting counts --> Worse batting counts lead to a lower pct. of fastballs. That seems more reasonable than a league-wide effort to throw more breaking pitches in the second half.
nada012
10/02
There's not a big correlation between overall offensive performance by TAv/OPS and fastball percentage. But it's a reasonable suggestion to look into in more detail. Parsing fastball % by count before and after seems like a good next step (as well as looking at swing rate).
redsoxin2004
10/02
Is it possible there was a larger, league-wide trend towards fewer fastballs? Did other teams also see a drop in frequency of fastballs?
nada012
10/02
Possible, but not supported by the data:
first half fastball percentage, leaguewide: 55.2%
second half fastball percentage, leaguewide: 55.5%

I looked at a few other teams and no, none of them saw drops nearly as dramatic as Oakland.
Behemoth
10/02
It seems odd that you wouldn't see a more gradual drop-off. A sudden fall would seem to require a lot of pitchers across a range of teams realising simultaneously that throwing fewer fastballs against the As was a winning strategy.
therealn0d
10/02
Or advance scouts catching onto something.
Behemoth
10/03
Just surprises me that all the advance scouts would realise the same thing at the same time.
therealn0d
10/03
It wouldn't occur at the same time. The A's don't face all the teams at the same time. Advance scouts would be seeing what previous advance scouts were seeing, until something changed. Therefore it wouldn't be simultaneous...scouts noticing that the A's are flailing would notice it in succession.
Shauntell
10/02
"(The A's) failing for no other reason than six inches of Josh Donaldson's positioning and tremendously poor injury luck".
The game should have been won earlier on. Bob Melvin has to be designated as the main culprit for this loss. I still can't believe one of the smartest teams in baseball would let their starter put on three base runners in the 8th inning, it's just absurd!
timber
10/02
But...but...but...Dalls Braden assured us most emphatically that Melvin made zero errors all night!
Richie
10/02
Good stuff, good analysis along with it. Thank you.
kenarneson
10/02
"either 1) Oakland was doing especially well against fastballs or 2) Oakland was doing especially poorly against non-fastballs."

My observation as an A's fan who watched all those painful games is that I think it's just the opposite: that several players (Moss, Crisp, Donaldson, Norris--but especially Moss) were playing hurt, and having trouble catching up to the fastball. And so they started cheating on the fastball, which made them vulnerable to chasing the offspeed stuff. The breaking stuff out of the zone that the A's lineup usually spit on, they suddenly were swinging at.

The one-strike fastball that was usually hit hard and put in play was missed or fouled off. And now the at-bat has an extra pitch--a two-strike pitch where the batter has to gear up and cheat a bit to get to that fastball he just missed, and here comes the curveball or changeup, often for strike three.
nada012
10/02
Interesting idea, I wonder if looking at swing rates might be helpful.
therealn0d
10/02
I was also thinking pitches seen per plate appearance.
kenarneson
10/02
If my hypothesis is right, the contact rate on fastballs in the zone should have gone down, and the swing rate on offspeed stuff out of the zone should have gone up.
Worthing
10/02
I had a similar experience as Ken watching most of the games down the stretch. Maybe it's just rationalizing and selective memory, but the number of fastballs just missed by Moss and Donaldson, especially Donaldson, really stands out. Are foul balls tracked by location? I'd swear every game Donaldson fouled a ball straight back to the backstop (followed by Glen saying "just missed that one").
walrus0909
10/02
What did they see instead? More breaking balls? Were pitchers trying to induce grounders from a team that (if I remember right) has a lot of fly ball hitters?
nada012
10/02
Caveat: I am using the MLBAM classifications for this, and to really be accurate, I'd need to get Harry's classifications. It's probably not an issue for assigning fastball vs. non-fastball, but getting into specific types can be troublesome without better data.

But, with that said: changeups up (a lot), curveballs a bit, and a marked increase in sinkers, maybe supporting your point.

I will say that sinker frequency increasing is a league-wide trend I've noticed, so I'm not sure if it's specific to Oakland, but intriguing nonetheless.

Weirdly, eephuses increased three-fold to ~.1% in the second half. Probably a classification error, but it would be cool if it was real.
therealn0d
10/02
"getting into specific types can be troublesome without better data."

Yes. The pitch types come with confidence %. It's an algorithm that ultimately determines the pitch type, amirite?
nada012
10/03
Yeah, it's a neural net. But I prefer Harry Pavlidis' brain to the MLBAM algorithm.
markpadden
10/03
That would be strange, since an article on BP this past winter showed that groundball pitchers fare worse (than expected) against flyball hitters, of which the A's team is almost entirely comprised. Based on that research, I would not think throwing an unusually high pct. of sinkers would work well against the A's.
pmahler
10/02
We also attended a lot of A's games this year, and the other thing that appeared to happen is that teams moved their outfield in in the second half. So soft hits that feel early in the year became outs. Is there a defensive alignment/position chart that would show if this was true?